Synchronization of Frame Rate to a Detected Cadence in a Time Lapse Image Sequence Using Sampling

ABSTRACT

A frame rate is synchronized to a detected cadence in order to generate an output image sequence that is substantially stabilized. In an in-camera process, a camera receives motion data of the camera while the camera captures the sequence of image frames. A dominant frequency of motion is determined and the capture frame rate is dynamically adjusted to match the frequency of detected motion so that each image frame is captured when the camera is at approximately the same position along the axis of motion. Alternatively, in a post-processing process, frames of a captured image sequence are selectively sampled at a sampling rate corresponding to the dominant frequency of motion so that each sampled frame corresponds to an image capture that occurred when the camera is at approximately the same position along the axis of motion.

BACKGROUND

Technical Field

This disclosure relates to digital photography, and more specifically,to synchronizing a frame rate of a time lapse image sequence.

Description of the Related Art

Action cameras may capture a variety of activities, such as sports andaction sequences, which are performed by users. When the action camerais mounted to the user, some activities introduce relatively highamplitude motion that results in unstabilized video or image sequences.Examples of such activities include running, biking, swimming,equestrian sports, and so on. During running, for example, the runningmotion creates a rhythmic up and down movement that results in arecording that has an undesirable vertical motion as the camera moves upand down after each step. A similar problem may occur when a camera ismounted to a moving object such as an automobile, motorcycle, bicycle,or flying vehicle (e.g., an unmanned aerial vehicle).

BRIEF DESCRIPTIONS OF THE DRAWINGS

The disclosed embodiments have other advantages and features which willbe more readily apparent from the following detailed description of theinvention and the appended claims, when taken in conjunction with theaccompanying drawings, in which:

FIG. 1 illustrates an example embodiment of a media processing system.

FIG. 2 illustrates an example architecture of a camera.

FIG. 3 illustrates exemplary graphs of motion data in a time domain andconverted to a frequency domain.

FIG. 4 illustrates an example embodiment of a process for synchronizinga frame rate to a detected cadence during a recording in real time.

FIG. 5 illustrates an example embodiment of a process for synchronizinga frame rate to a detected cadence in post processing.

DETAILED DESCRIPTION

The figures and the following description relate to preferredembodiments by way of illustration only. It should be noted that fromthe following discussion, alternative embodiments of the structures andmethods disclosed herein will be readily recognized as viablealternatives that may be employed without departing from the principlesof what is claimed.

Reference will now be made in detail to several embodiments, examples ofwhich are illustrated in the accompanying figures. It is noted thatwherever practicable similar or like reference numbers may be used inthe figures and may indicate similar or like functionality. The figuresdepict embodiments of the disclosed system (or method) for purposes ofillustration only. One skilled in the art will readily recognize fromthe following description that alternative embodiments of the structuresand methods illustrated herein may be employed without departing fromthe principles described herein.

Configuration Overview

In a first embodiment, camera dynamically synchronizes a frame rate to adetected cadence by adjusting the frame rate during image capture. Acamera is configured to operate according to an initial frame rate. Acapture of a time lapse image sequence is initiated on the cameraaccording to the initial frame rate. Motion data of the camera isrecorded during the capture of the time lapse image sequence by one ormore sensors tracking motion of the camera while the camera captures thetime lapse image sequence. The motion data in a particular window oftime is converted from time domain data to frequency domain data. Adominant frequency is determined in the frequency domain data. Amodified frame rate is then determined that is within a predefinedtolerance range of the dominant frequency. Capture of the time lapseimage sequence is then continued according to the modified frame rate.

In a second embodiment, a frame rate is synchronized to a detectedcadence in post-processing by selectively sampling frames of thecaptured image sequence. A sequence of image frames having a first framerate is received. Motion data of a camera recorded is also received fromone or more sensors tracking motion of the camera while the cameracaptures the sequence of image frames. The motion data in a particularwindow of time is converted from time domain data to frequency domaindata. A dominant frequency in the frequency domain data is determinedfor the particular window of time. Frames are then sampled from thesequence of image frames in the particular window of time that are at asampling frequency that is within a predefined tolerance of the dominantfrequency. A new image sequence is created with the sampled frames.

Example Media Processing System

FIG. 1 is a block diagram of a media processing system 100, according toone embodiment. The media content system 100 includes a network 120, acamera 130, a client device 135 and a video server 140. In alternativeconfigurations, different and/or additional components may be includedin the media content system 100.

The camera 130 comprises a camera body, one or more a camera lenses,various indicators on the camera body (such as LEDs, displays, and thelike), various input mechanisms (such as buttons, switches, andtouch-screen mechanisms), and electronics (e.g., imaging electronics,power electronics, metadata sensors, etc.) internal to the camera bodyfor capturing images via the one or more lenses and/or performing otherfunctions. In embodiment, the camera 130 is mounted to a user using, forexample, a helmet or head mount, chest mount, or wrist mount. In anotherembodiment, the camera 130 is mounted to a moving object such as anautomobile, motorcycle, bicycle, or flying vehicle (e.g., an unmannedaerial vehicle).

As described in greater detail in conjunction with FIG. 2 below, thecamera 130 can include sensors to capture metadata associated with videodata, such as timing data, motion data, speed data, acceleration data,altitude data, GPS data, 3D positional data, and the like. In aparticular embodiment, position, motion, and/or time centric metadata(time, position, speed, etc.) can be incorporated into a media filetogether with the captured content in order to track position ormovement of the camera 130 over time. This metadata may be captured bythe camera 130 itself or by another device (e.g., a mobile phone)proximate to the camera 130 or physically coupled to the camera 130. Inone embodiment, the metadata may be incorporated with the content streamby the camera 130 as the content is being captured. In anotherembodiment, a metadata file separate from the video file may be captured(by the same capture device or a different capture device) and the twoseparate files can be combined or otherwise processed together inpost-processing.

The video server 140 receives and stores images and videos captured bythe camera 130 and allows users to access the images and videos at alater time. In one embodiment, the video server 140 provides the userwith an interface, such as a web page or native application installed onthe client device 135, to interact with and/or edit the stored imagesand videos. A user can interact with interfaces provided by the videoserver 140 via the client device 135. The client device 135 is anycomputing device capable of receiving user inputs as well astransmitting and/or receiving data via the network 120. In oneembodiment, the client device 135 is a conventional computer system,such as a desktop or a laptop computer. Alternatively, the client device135 may be a device having computer functionality, such as a personaldigital assistant (PDA), a mobile telephone, a smartphone or anothersuitable device. The user can use the client device 135 to view andinteract with or edit images and videos stored on the video server 140.

In one embodiment, the client device 135 interacts with the video server140 through an application programming interface (API) running on anative operating system of the client device 135, such as IOS® orANDROID™. While FIG. 1 shows a single client device 135, in variousembodiments, any number of client devices 135 may communicate with thevideo server 140.

The video server 140 communicates with the client device 135 and/or thecamera 130 via the network 120, which may include any combination oflocal area and/or wide area networks, using both wired and/or wirelesscommunication systems. In one embodiment, the network 120 uses standardcommunications technologies and/or protocols. In some embodiments, allor some of the communication links of the network 120 may be encryptedusing any suitable technique or techniques. It should be noted that insome embodiments, the functionalities attributed to the video server 140may instead be performed by the camera 130 or the client device 135.

Various components of the environment 100 of FIG. 1 such as the camera130, video server 140, and client device 125 can include one or moreprocessors and a non-transitory computer-readable storage medium storinginstructions therein that when executed cause the processor to carry outthe functions attributed to the respective devices described herein.

Example Camera Configuration

FIG. 2 is a block diagram illustrating a camera 130, according to oneembodiment. In the illustrated embodiment, the camera 130 comprises acamera core 210 comprising a lens 212, an image sensor 214, and an imageprocessor 216. The camera 130 additionally includes a system controller220 (e.g., a microcontroller or microprocessor) that controls theoperation and functionality of the camera 130 and system memory 230configured to store executable computer instructions that, when executedby the system controller 220 and/or the image processors 216, performthe camera functionalities described herein. In some embodiments, thesystem memory 230 stores a frame synchronization module 217 and framesynchronization data 231.

The lens 212 can be, for example, a standard lens, wide angle lens,hemispherical, or hyperhemispherical lens that focuses light enteringthe lens to the image sensor 214 which captures images and/or videoframes. The image sensor 214 may capture high-definition images having aresolution of, for example, 720p, 1080p, 4k, or higher. The imageprocessor 216 performs one or more image processing functions of thecaptured images or video. For example, the image processor 216 mayperform a Bayer transformation, demosaicing, noise reduction, imagesharpening, image stabilization, rolling shutter artifact reduction,color space conversion, compression, or other in-camera processingfunctions. Processed images and video may be temporarily or persistentlystored to system memory 230 and/or to a non-volatile storage, which maybe in the form of internal storage or an external memory card.

An input/output (I/O) interface 260 transmits and receives data fromvarious external devices. For example, the I/O interface 260 mayfacilitate the receiving or transmitting video or audio informationthrough an I/O port. Examples of I/O ports or interfaces include USBports, HDMI ports, Ethernet ports, audioports, and the like.Furthermore, embodiments of the I/O interface 260 may include wirelessports that can accommodate wireless connections. Examples of wirelessports include Bluetooth, Wireless USB, Near Field Communication (NFC),and the like. The I/O interface 260 may also include an interface tosynchronize the camera 130 with other cameras or with other externaldevices, such as a remote control, a second camera 130, a smartphone, aclient device 135, or a video server 140.

A control/display subsystem 270 includes various control and displaycomponents associated with operation of the camera 130 including, forexample, LED lights, a display, buttons, microphones, speakers, and thelike. The audio subsystem 250 includes, for example, one or moremicrophones and one or more audio processors to capture and processaudio data correlated with video capture. In one embodiment, the audiosubsystem 250 includes a microphone array having two or microphonesarranged to obtain directional audio signals.

In one embodiment, the camera 130 captures an image sequence as a timelapse image sequence. Here, the camera 130 captures a single framebetween fixed intervals of time. The time-lapse recording may be playedback (or rendered into a video) at a standard video frame rate equal(e.g., 30 fps or 60 fps) that may be substantially higher than the timelapse frame rate, In this case the output video will have the effect ofplaying back compressed in time, such that the time to play back thevideo is accelerated relative to the time it took to capture the imagesequence. In an alternative embodiment, the same effect can be generatedby capturing a video with a standard frame rate (e.g., 30 fps or 60 fps)and then retaining only a subset of frames (e.g., every x frames) whilediscarding the remaining frames so as to compress the video in time.This produces an effect similar to the time lapse effect describedabove.

The sensors 240 capture various metadata concurrently with, orseparately from, image and video capture. For example, the sensors 240may capture time-stamped position, orientation, and/or motion data andmay include, for example, an orientation sensor, an accelerometer, agyroscope, or a magnetometer. Sensor data captured from the varioussensors 240 may be processed to generate other types of metadata. Forexample, sensor data from the accelerometer may be used to generatemotion metadata, comprising velocity and/or acceleration vectorsrepresentative of motion of the camera 130. Furthermore, sensor datafrom the may be used to generate orientation metadata describing theorientation of the camera 130. In one embodiment, the sensors 240 arerigidly coupled to the camera 130 such that any motion, orientation orchange in location experienced by the camera 130 is also experienced bythe sensors 240. In an alternative embodiment, the sensors 240 may beintegrated with a different device other than the camera 130 itself. Forexample, the sensors 240 may be integrated with an unmanned aerialvehicle carrying the camera 130 and provide the sensor data to thecamera 130.

The sensors 240 furthermore may associate a time stamp representing whenthe data was captured by each sensor. In one embodiment, the sensors 240automatically begin collecting sensor metadata when the camera 130begins to record a video or capture images. The sensor data may becorrelated to different frames of the time lapse or video capture suchthat each frame is associated with motion and/or position datadescribing the motion and/or position of the camera 130 at the time thatframe was captured. This data may be stored as frame synchronizationdata 231, which may comprise the sensor data, positional data, frequencydomain conversions, and other data used by the frame synchronizationmodule 217 used to synchronize frame rate as will be described infurther detail below.

In one embodiment, the system memory 230 stores a frame synchronizationmodule 217 that facilitates synchronization of the frame rate with adetected cadence. While the camera 130 is recording video or time lapseimages, the camera 130 may undergo motion that causes an unstabilizedoutput image sequence. For example, during certain activities such asrunning, jogging, horseback riding, or so on when the camera 130 ismounted to the user, the camera may experience up and down movementbased on a cadence of the motion. In the case of running, for example,the cadence of the runner may correspond to the runner's step rate,which is translated to oscillating movement of the user-mounted camera130. If the motion is substantially sinusoidal over time as is generallythe case with a runner moving at an approximately constant pace andsteady gait, the frame synchronization module 217 can detect thefrequency of this oscillation, and adjust the capture frame rate so thateach frame is captured when the camera 130 is at approximately the samevertical position (e.g., at the bottom of the gait each time a foot hitsthe ground). The results in an image sequence that is substantiallystabilized. In other use case scenarios when the camera is mounted to anunmanned aerial vehicle or other moving object, the cadence maycorrespond to a natural oscillation in the movement of the object (e.g.,up and down movement, side-to-side movement, or both). This oscillationfrequency may similarly be detected and the frame rate adjusted so thateach frame is captured when the camera 130 is at approximately the sameposition along the axis of oscillation, thus resulting in asubstantially stabilized image sequence.

In another embodiment, the frame synchronization module 217 insteadoperates on a buffered window of frames and selectively retaining onlyframes that were captured when the camera 130 was at a particularposition along the axis of oscillation and discarding other frames,similarly resulting in an image sequence that is substantiallystabilized. The frame synchronization module 217 may periodically adjustthe frame rate as the cadence changes. An additional effect of thisframe rate synchronization is that the capture frame rate tends toincrease as the user or object on which the camera is attached movesfaster and the capture frame rate tends to decrease as the user orobject moves slower. Thus, the length of the output image sequence maybe more closely tied to the number of steps covered regardless of theuser's or object's speed.

In one embodiment, the frame synchronization module 217 computespositional data (relative to a fixed point in space) based on the framesynchronization data 231 from the sensors 240. For example, thesynchronization module 217 may determine changes in direction based onthe data recorded by the accelerometer, and estimate the resulting speedand/or position based on the amount of acceleration recorded. In oneembodiment, the frame synchronization module 217 computes the positionaldata in real time during the recording process. When computing thepositional data in real time, the frame synchronization module 217 usesthe prior and current sensor data to determine the current position ofthe camera 130. In other embodiments, the frame synchronization module217 computes the positional data from the accelerometer data after therecording is concluded in a post-processing step. In another embodiment,positional data is not necessarily computed and the framesynchronization module 217 may determine the frame rate based directlyon acceleration or velocity data. In yet other embodiments, positionaldata is obtained from a velocity or position sensor instead of anaccelerometer.

In one embodiment, the camera 130 may adjust the sampling rate of thesensor data to ensure that the sampling rate exceeds the Nyquistfrequency for an expected maximum cadence. The Nyquist frequency for thesystem may be determined a priori by experimentation based on themaximum cadence measured for any activity and be set to this fixedvalue. Multiple different sampling frequencies may be programmable orautomatically selected based on different factors, such as the currentspeed of the camera 130. In one embodiment, the frame synchronizationmodule 217 interpolates the sensor data such that the sampling rate isabove a rate to perform a proper frequency domain analysis of thepositional data.

In one embodiment, a frequency analysis is performed on the sensor data.For example, the frame synchronization module 217 may convert the timedomain positional data to a frequency domain using, for example, adiscrete Fourier transform that may be implemented using a fast Fouriertransform algorithm (e.g., Cooley-Tukey). In one embodiment, the framesynchronization module 217 performs the Fourier transform in real timeon small slices (e.g., a predetermined number of frames or timeinterval) of positional data as the data is determined in real time fromreal time sensor data. In one embodiment, the frame synchronizationmodule 217 performs the Fourier transform subsequent to the completionof the recording.

After converting the positional data to the frequency domain, the framesynchronization module 217 determines the frequency of the oscillationsusing the converted positional data. In one embodiment, only thedominant frequency having the largest magnitude of the positional datais used. In another embodiment, when multiple frequencies havemagnitudes within a certain range of the dominant frequency, and whenthese multiple frequencies are within a certain frequency range of eachother, the frame synchronization module 217 may take the averagefrequency of those multiple frequencies along with the dominantfrequency, and selects this average frequency as the dominant frequencythat represents the frequency of the detected cadence.

Once the frequency of the oscillations is determined, the framesynchronization module 217 modifies the interval of the time-lapse imagesequence such that each frame of the time-lapse image sequencecorresponds to a capture frame rate similar to the detected frequency ofthe oscillations. In this way, the frames of the recording will becaptured at a similar vertical position, and the effect of theoscillations on the recording are diminished. To better match thefrequency of the oscillations, in one embodiment, the framesynchronization module 217 increases the capture interval when thefrequency of the oscillations is determined to be lower than thefrequency of the current frame rate of the recording (i.e.,time/interval>oscillation frequency), and decreases the interval whenthe frequency of the oscillations is determined to be higher than thefrequency of the current frame rate of the recording.

In one embodiment, the interval is adjusted periodically duringrecording based on a prior window of time such that the rate of capturefor frames may change over time based on changes in the oscillationfrequency (e.g., due to a runner or object on which the camera ismounted changing pace). In other embodiments, where the frames areselected in post-processing instead of during capture, the framesynchronization module 217 modifies the interval between the retainedframes for different frame ranges in order to match detected changes inthe cadence. Here, the frame synchronization module 217 may analyze therecorded video by sections, and apply a different interval to eachsection based on the dominant frequency in that section as recorded inthe sensor data.

In one embodiment, the frame synchronization module 217 and framesynchronization data 231 resides on a server or client device (e.g.,video server 140 or client device 135) instead of the camera 130. Inthis embodiment, the server or client device having the framesynchronization module 217 receives the recorded frames (i.e., therecording or time lapse image frames) and motion data to perform thesynchronization of the frame rate to the cadence in post-processing.

Exemplary Positional Data in Time and Frequency Domain

FIG. 3 illustrates exemplary graphs of positional data in a time domain300 and converted to a frequency domain 350. The graphs 300 and 350 areintended for illustrative purposes only, and are not necessarily drawnto scale and are not necessarily mathematically accurate. Graph 300illustrates exemplary positional data recorded during a window of timethat may be part of a larger recording session as described above. Here,the positional data represents relative position of the camera 130 in avertical direction over time. As illustrated, the positional data ingraph 300 indicates movement of the camera 130 having a fundamentaloscillation period of approximately one second. This might correspond toa slow jog or brisk walking motion of the user that the camera 130 isattached to at a pace of approximately one step per second in which eachlocal minimum may roughly correspond to time instances when the user'sfoot hits the ground and each local maximum may roughly correspond toinstances between steps when the user is at the peak of his or her gait.Different oscillation periods may be applicable when the camera 130 isattached to an unmanned aerial vehicle or other moving object.

Graph 350 illustrates the positive portion of the frequency domainconversion of the data in graph 300. The data may be converted in thesame manner as described above (e.g., by fast Fourier transform). Amaximum value is seen at approximately 1 Hz, corresponding to thefundamental period of the time-domain data in graph 300. The frame rateof the image sequence can then be modified to match the determinedfundamental frequency associated with the camera movement. As will beapparent from the graph 300, if a frame is captured once per second, thevertical position of the camera 130 at the time of capture will remainapproximately constant, thereby resulting in substantially stabilizedimage sequence. This frequency analysis and frame rate adjustment may bere-performed in subsequent time windows so as to periodically adjust asthe frequency of the camera movement changes over time (e.g., when arunner slows down or speeds up).

Process for Synchronizing a Frame Rate to a Detected Cadence DuringImage Capture

FIG. 4 illustrates an example embodiment of a process for synchronizinga frame rate to a detected cadence during image capture. In someembodiments, the process is performed by the camera 130 and may beperformed in real-time or approximately real-time. In some embodiments,the order and/or operations in the process are different thanillustrated here.

The camera 130 initiates 402 a time lapse image capture with an initialinterval between each frame of the recording. While capturing images,the camera 130 also continuously records 404 motion data of the camera130 (e.g., motion along a vertical axis perpendicular to the ground orother axis of oscillation) representing motion of the camera 130 duringthe time lapse image capture. This motion data may be recorded by thesensors of the camera 130 or derived from the sensor data. Periodically,the camera 130 converts 406 the motion data in a particular window oftime from time domain data to frequency domain data. The camera 130determines 408 the dominant frequency in the frequency domain data. Inone embodiment, the dominant frequency is the frequency with the highestmagnitude value. The camera then modifies 410 the time lapse interval toreduce the difference between the frame rate and the dominant frequency.For example, the camera 130 may set a new interval between image framessuch that subsequent frames are captured at a frequency thatsubstantially matches (e.g., is within a predefined tolerance) of thedominant frequency. Alternatively, in order to provide smoothertransitions, a filter may be applied so that the camera 130incrementally adjusts the frame rate to bring it closer to the dominantfrequency without necessarily making a significant discontinuous jump inframe rate. This process repeats until the image capture ends.

Process for Synchronizing a Frame Rate to a Detected Cadence in PostProcessing

FIG. 5 illustrates an example embodiment of a process for synchronizinga frame rate to a detected cadence in post processing. In someembodiments, the process is performed by the camera 130. In someembodiments, the order and/or operations in the process are differentthan illustrated here.

The camera 130 initiates 502 a video recording or time lapse imagecapture at a frame rate significantly higher than the expected cadencefrequency (e.g., 30 fps, 60 fps, 120 fps). The camera 130 also records504 motion data (e.g., motion along a vertical axis perpendicular to theground) representing motion of the camera 130 during image or videocapture. Subsequently, the camera 130 ends 506 capture of the video ortime lapse image sequence. For a given range of frames, the camera 130converts 508 the recorded motion data from time domain data to frequencydomain data. The camera 130 determines 510 the dominant frequency in thefrequency domain data in the given range of frames, and then selects 512frames that are taken at a frequency that substantially matches thedominant frequency of the detected cadence (e.g., is within a predefinedtolerance of the dominant frequency). This process may be repeated foradditional frame ranges so that the effective frame rate may change overtime. Subsequently, the camera 130 creates 514 a new video with theselected frames.

In one embodiment, the process described here for synchronizing a framerate to a detected cadence in post processing is performed on anexternal entity, such as a server or client device. The external entityreceives the recording or time lapse image capture and motion data fromthe camera and performs the steps described herein to perform thesynchronization.

Alternative Process for Synchronizing a Frame Rate to a Detected Cadence

In one embodiment, instead of performing a frequency domain analysis onthe motion data, the camera 130 instead captures or selects the framesthat occur when the motion data indicates a certain position (orindicates a position in a defined range) of the camera. Using thisprocess, the frames of the recording or time lapse are all captured atthe same camera position, which diminishes the effect of theoscillations due to the motion of the camera 130.

Additional Configuration Considerations

Throughout this specification, some embodiments have used the expression“coupled” along with its derivatives. The term “coupled” as used hereinis not necessarily limited to two or more elements being in directphysical or electrical contact. Rather, the term “coupled” may alsoencompass two or more elements are not in direct contact with eachother, but yet still co-operate or interact with each other.

Likewise, as used herein, the terms “comprises,” “comprising,”“includes,” “including,” “has,” “having” or any other variation thereof,are intended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of elements is notnecessarily limited to only those elements but may include otherelements not expressly listed or inherent to such process, method,article, or apparatus.

In addition, use of the “a” or “an” are employed to describe elementsand components of the embodiments herein. This is done merely forconvenience and to give a general sense of the invention. Thisdescription should be read to include one or at least one and thesingular also includes the plural unless it is obvious that it is meantotherwise.

Finally, as used herein any reference to “one embodiment” or “anembodiment” means that a particular element, feature, structure, orcharacteristic described in connection with the embodiment is includedin at least one embodiment. The appearances of the phrase “in oneembodiment” in various places in the specification are not necessarilyall referring to the same embodiment.

Upon reading this disclosure, those of skill in the art will appreciatestill additional alternative structural and functional designs for thedescribed embodiments as disclosed from the principles herein. Thus,while particular embodiments and applications have been illustrated anddescribed, it is to be understood that the disclosed embodiments are notlimited to the precise construction and components disclosed herein.Various modifications, changes and variations, which will be apparent tothose skilled in the art, may be made in the arrangement, operation anddetails of the method and apparatus disclosed herein without departingfrom the scope defined in the appended claims.

What is claimed is:
 1. A method for synchronization of a frame rate to adetected cadence, the method comprising: receiving a sequence of imageframes having a first frame rate; receiving motion data of a camerarecorded by one or more sensors tracking motion of the camera while thecamera captures the sequence of image frames; converting the motion datain a particular window of time from time domain data to frequency domaindata; determining a dominant frequency in the frequency domain data forthe particular window of time; sampling frames from the sequence ofimage frames in the particular window of time that are at a samplingfrequency that is within a predefined tolerance of the dominantfrequency; and creating a new image sequence with the sampled frames. 2.The method of claim 1, wherein the particular window of time comprises apredefined time window.
 3. The method of claim 1, wherein the motiondata comprises position data along an axis of oscillation derived fromsensed data captured by a motion sensor of the camera.
 4. The method ofclaim 1, wherein the converting the motion data from time domain data tofrequency domain data is performed using Fast Fourier Transform.
 5. Themethod of claim 1, wherein the determining the dominant frequency in thefrequency domain data comprises: determining a frequency value in thefrequency domain data that has the largest amplitude of the plurality offrequency values in the frequency domain data; selecting the frequencyvalue as the dominant frequency.
 6. The method of claim 1, whereinsampling frames from the sequence of image frames comprises: samplingframes from the sequence of image frames at a sampling frequency thatmatches the dominant frequency.
 7. A non-transitory computer-readablestorage medium storing instructions for synchronization of frame rate tocadence, the instructions when executed by one or more processors causethe one or more processors to: receive a sequence of image frames havinga first frame rate; receive motion data of a camera recorded by one ormore sensors tracking motion of the camera while the camera captures thesequence of image frames; convert the motion data in a particular windowof time from time domain data to frequency domain data; determine adominant frequency in the frequency domain data for the particularwindow of time; sample frames from the sequence of image frames in theparticular window of time that are at a sampling frequency that iswithin a predefined tolerance of the dominant frequency; and create anew image sequence with the sampled frames.
 8. The non-transitorycomputer-readable storage medium of claim 7, wherein the particularwindow of time comprises a predefined time window.
 9. The non-transitorycomputer-readable storage medium of claim 7, wherein the motion datacomprises position data along an axis of oscillation derived from senseddata captured by a motion sensor.
 10. The non-transitorycomputer-readable storage medium of claim 7, wherein the conversion ofthe motion data from time domain data to frequency domain data isperformed using Fast Fourier Transform.
 11. The non-transitorycomputer-readable storage medium of claim 7, wherein thecomputer-readable storage medium stores further instructions for thedetermination of the dominant frequency in the frequency domain data,the instructions when executed by the one or more processors cause theone or more processors to: determine a frequency value in the frequencydomain data that has the largest amplitude of the plurality of frequencyvalues in the frequency domain data; select the frequency value as thedominant frequency.
 12. The non-transitory computer-readable storagemedium of claim 7, wherein the computer-readable storage medium storesfurther instructions for the sampling of frames from the sequence ofimage frames, the instructions when executed by the one or moreprocessors cause the one or more processors to: sample frames from thesequence of image frames at a sampling frequency that matches thedominant frequency.
 13. A computing device, comprising: one or moreprocessors; and a non-transitory computer-readable storage mediumstoring instructions, the instructions when executed by one or moreprocessors causing the one or more processors to perform stepsincluding: receiving a sequence of image frames having a first framerate; receiving motion data of a camera recorded by one or more sensorstracking motion of the camera while the camera captures the sequence ofimage frames; converting the motion data in a particular window of timefrom time domain data to frequency domain data; determining a dominantfrequency in the frequency domain data for the particular window oftime; sampling frames from the sequence of image frames in theparticular window of time that are at a sampling frequency that iswithin a predefined tolerance of the dominant frequency; and creating anew image sequence with the sampled frames.
 14. The device of claim 13,wherein the particular window of time comprises a predefined timewindow.
 15. The device of claim 13, wherein the motion data comprisesposition data along an axis of oscillation derived from sensed datacaptured by a motion sensor.
 16. The device of claim 13, wherein theconversion of the motion data from time domain data to frequency domaindata is performed using Fast Fourier Transform.
 17. The device of claim13, wherein the computer-readable storage medium stores furtherinstructions for the determination of the dominant frequency in thefrequency domain data from the particular window of time, theinstructions when executed by the one or more processors causing theprocessors to perform steps including: determining a frequency value inthe frequency domain data from the particular window of time that hasthe largest amplitude of the plurality of frequency values in thefrequency domain data; selecting the frequency value as the dominantfrequency.
 18. The device of claim 13, wherein the computer-readablestorage medium stores further instructions for the sampling of theframes from the time lapse image sequence, the instructions whenexecuted by the one or more processors causing the processors to performsteps including: sampling frames from the sequence of image frames at asampling frequency that matches the dominant frequency.